Adaptive Fuzzy-Lyapunov Controller Using Biologically Inspired Swarm Intelligence

The collective behaviour of swarms produces smarter actions than those achieved by a single individual. Colonies of ants, flocks of birds and fish schools are examples of swarms interacting with their environment to achieve a common goal. This cooperative biological intelligence is the inspiration f...

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Main Authors: Alejandro Carrasco Elizalde, Peter Goldsmith
Format: Article
Language:English
Published: Wiley 2008-01-01
Series:Applied Bionics and Biomechanics
Online Access:http://dx.doi.org/10.1080/11762320802027869
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author Alejandro Carrasco Elizalde
Peter Goldsmith
author_facet Alejandro Carrasco Elizalde
Peter Goldsmith
author_sort Alejandro Carrasco Elizalde
collection DOAJ
description The collective behaviour of swarms produces smarter actions than those achieved by a single individual. Colonies of ants, flocks of birds and fish schools are examples of swarms interacting with their environment to achieve a common goal. This cooperative biological intelligence is the inspiration for an adaptive fuzzy controller developed in this paper. Swarm intelligence is used to adjust the parameters of the membership functions used in the adaptive fuzzy controller. The rules of the controller are designed using a computing-with-words approach called Fuzzy-Lyapunov synthesis to improve the stability and robustness of an adaptive fuzzy controller. Computing-with-words provides a powerful tool to manipulate numbers and symbols, like words in a natural language.
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spelling doaj-art-4ce9c3d98c0746509b29b0c9823499822025-08-20T03:34:19ZengWileyApplied Bionics and Biomechanics1176-23221754-21032008-01-0151334610.1080/11762320802027869Adaptive Fuzzy-Lyapunov Controller Using Biologically Inspired Swarm IntelligenceAlejandro Carrasco Elizalde0Peter Goldsmith1Department of Mechanical and Manufacturing Engineering, University of Calgary, 2500 University Drive N. W., CanadaDepartment of Mechanical and Manufacturing Engineering, University of Calgary, 2500 University Drive N. W., CanadaThe collective behaviour of swarms produces smarter actions than those achieved by a single individual. Colonies of ants, flocks of birds and fish schools are examples of swarms interacting with their environment to achieve a common goal. This cooperative biological intelligence is the inspiration for an adaptive fuzzy controller developed in this paper. Swarm intelligence is used to adjust the parameters of the membership functions used in the adaptive fuzzy controller. The rules of the controller are designed using a computing-with-words approach called Fuzzy-Lyapunov synthesis to improve the stability and robustness of an adaptive fuzzy controller. Computing-with-words provides a powerful tool to manipulate numbers and symbols, like words in a natural language.http://dx.doi.org/10.1080/11762320802027869
spellingShingle Alejandro Carrasco Elizalde
Peter Goldsmith
Adaptive Fuzzy-Lyapunov Controller Using Biologically Inspired Swarm Intelligence
Applied Bionics and Biomechanics
title Adaptive Fuzzy-Lyapunov Controller Using Biologically Inspired Swarm Intelligence
title_full Adaptive Fuzzy-Lyapunov Controller Using Biologically Inspired Swarm Intelligence
title_fullStr Adaptive Fuzzy-Lyapunov Controller Using Biologically Inspired Swarm Intelligence
title_full_unstemmed Adaptive Fuzzy-Lyapunov Controller Using Biologically Inspired Swarm Intelligence
title_short Adaptive Fuzzy-Lyapunov Controller Using Biologically Inspired Swarm Intelligence
title_sort adaptive fuzzy lyapunov controller using biologically inspired swarm intelligence
url http://dx.doi.org/10.1080/11762320802027869
work_keys_str_mv AT alejandrocarrascoelizalde adaptivefuzzylyapunovcontrollerusingbiologicallyinspiredswarmintelligence
AT petergoldsmith adaptivefuzzylyapunovcontrollerusingbiologicallyinspiredswarmintelligence